This commit replaces the Python implementation of the tokenize module with an implementation
that reuses the real C tokenizer via a private extension module. The tokenize module now implements
a compatibility layer that transforms tokens from the C tokenizer into Python tokenize tokens for backward
compatibility.
As the C tokenizer does not emit some tokens that the Python tokenizer provides (such as comments and non-semantic newlines), a new special mode has been added to the C tokenizer mode that currently is only used via
the extension module that exposes it to the Python layer. This new mode forces the C tokenizer to emit these new extra tokens and add the appropriate metadata that is needed to match the old Python implementation.
Co-authored-by: Pablo Galindo <pablogsal@gmail.com>
This implements PEP 695, Type Parameter Syntax. It adds support for:
- Generic functions (def func[T](): ...)
- Generic classes (class X[T](): ...)
- Type aliases (type X = ...)
- New scoping when the new syntax is used within a class body
- Compiler and interpreter changes to support the new syntax and scoping rules
Co-authored-by: Marc Mueller <30130371+cdce8p@users.noreply.github.com>
Co-authored-by: Eric Traut <eric@traut.com>
Co-authored-by: Larry Hastings <larry@hastings.org>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
When monitoring LINE events, instrument all instructions that can have a predecessor on a different line.
Then check that the a new line has been hit in the instrumentation code.
This brings the behavior closer to that of 3.11, simplifying implementation and porting of tools.
This PR removes `_Py_dg_stdnan` and `_Py_dg_infinity` in favour of
using the standard `NAN` and `INFINITY` macros provided by C99.
This change has the side-effect of fixing a bug on MIPS where the
hard-coded value used by `_Py_dg_stdnan` gave a signalling NaN
rather than a quiet NaN.
---------
Co-authored-by: Mark Dickinson <dickinsm@gmail.com>
This is the culmination of PEP 684 (and of my 8-year long multi-core Python project)!
Each subinterpreter may now be created with its own GIL (via Py_NewInterpreterFromConfig()). If not so configured then the interpreter will share with the main interpreter--the status quo since subinterpreters were added decades ago. The main interpreter always has its own GIL and subinterpreters from Py_NewInterpreter() will always share with the main interpreter.
We also add PyInterpreterState.ceval.own_gil to record if the interpreter actually has its own GIL.
Note that for now we don't actually respect own_gil; all interpreters still share the one GIL. However, PyInterpreterState.ceval.own_gil does reflect PyInterpreterConfig.own_gil. That lie is a temporary one that we will fix when the GIL really becomes per-interpreter.
Here we are doing no more than adding the value for Py_mod_multiple_interpreters and using it for stdlib modules. We will start checking for it in gh-104206 (once PyInterpreterState.ceval.own_gil is added in gh-104204).
In preparation for a per-interpreter GIL, we add PyInterpreterState.ceval.gil, set it to the shared GIL for each interpreter, and use that rather than using _PyRuntime.ceval.gil directly. Note that _PyRuntime.ceval.gil is still the actual GIL.
This function no longer makes sense, since its runtime parameter is
no longer used. Use directly _PyThreadState_GET() and
_PyInterpreterState_GET() instead.
This breaks the tests, but we are keeping it as a separate commit so
that the move operation and editing of the moved files are separate, for
a cleaner history.
We also expose PyInterpreterConfig. This is part of the PEP 684 (per-interpreter GIL) implementation. We will add docs as soon as we can.
FYI, I'm adding the new config field for per-interpreter GIL in gh-99114.
Marta Gómez Macías
Jelle Zijlstra
Mark Shannon
Carl Meyer
Brandt Bucher
Irit Katriel
Eric Snow
Erlend E. Aasland
Dong-hee Na
penguin_wwy
Sebastian Berg
Arthur Pastel
John Belmonte
Tomas R
Nikita Sobolev
Victor Stinner
Petr Viktorin
Tian Gao
Paul Ganssle